User Text Content Correlation with Location

Abstract

A predictive modelling system for predicting location data from user textual data comprising: an input for receiving user data, the user data comprising user textual data and location data; a pre-processing module arranged to correlate user textual data with location data to form a set of correlated data; a training module arranged to use the set of correlated data to train a machine learning algorithm such that the algorithm is arranged to output predicted location data from an input textual query.

1 . A system for predicting location data from user textual data, the system comprising:
 an input that receives user data, the user data comprising user textual data and location data;   a pre-processing module that clusters the location data into a plurality of cluster centers and that correlates the user textual data with the location data to form a set of correlated data; and   a training module that uses the set of correlated data to train a machine learning algorithm such that the algorithm outputs predicted location data from an input textual query.   
     
     
         2 . (canceled) 
     
     
         3 . The system of  claim 1 , wherein the user data is received from a device with a global positioning system (GPS). 
     
     
         4 . The system of  claim 3 , wherein the device with the GPS is a mobile communications device. 
     
     
         5 . The system of  claim 3 , wherein the device is a vehicle. 
     
     
         6 . (canceled) 
     
     
         7 . The system of  claim 1 , wherein the pre-processing module merges clusters of the location data when the cluster centers are within a predefined proximity to one another. 
     
     
         8 . The system of  claim 1 , wherein the pre-processing module classifies location data into fixed location categories and journey route categories. 
     
     
         9 . The system of  claim 8 , wherein the pre-processing module removes specific location data points if they have been classified as being part of a user journey route. 
     
     
         10 . The system of  claim 8 , wherein the training module trains the machine learning algorithm by dividing fixed location categories into two groups, the first group comprising a most popular fixed location category and the second group comprising all remaining categories, in order to reduce data skewing during training. 
     
     
         11 . The system of  claim 8 , wherein the training module trains the machine learning algorithm to optimize identification of local optima in the user data. 
     
     
         12 . The system of  claim 1 , wherein the training module splits the set of correlated data into a training portion for training the machine learning algorithm and a verification portion for verifying accuracy of the trained machine learning algorithm. 
     
     
         13 . The system of  claim 1 , wherein the machine learning algorithm outputs predicted location data and a confidence level associated with the predicted location data. 
     
     
         14 . A mobile network bandwidth planning system comprising the system of  claim 1 . 
     
     
         15 . A hybrid car battery charge management module comprising the system of  claim 1 . 
     
     
         16 . A system for predicting location data from user textual data, the system comprising:
 an input that receives user data, the user data comprising user textual data;   a pre-processing module that correlates the user textual data with location data to form a set of correlated data;   a training module that uses the set of correlated data to train a machine learning algorithm such that the algorithm outputs predicted location data from an input textual query; and   an output arranged to output the predicted location data for the user based on the received user textual data.   
     
     
         17 . A mobile network bandwidth planning system comprising the system of  claim 16 . 
     
     
         18 . A hybrid car battery charge management module comprising the system of  claim 16 . 
     
     
         19 . A method of training a machine learning algorithm, the method comprising:
 receiving user data, the user data comprising user textual data from a user calendar and location data;   clustering the location data into a plurality of cluster centers;   correlating the user textual data with the location data to form a set of correlated data;   using the set of correlated data to train a machine learning algorithm such that the algorithm outputs predicted location data from an input textual query.   
     
     
         20 . A non-transitory computer readable medium storing a computer program comprising computer readable code for controlling a computing device to carry out the method of  claim 19 . 
     
     
         21 - 22 . (canceled)